Bibliographic record
Abstract
Background: Necrotizing fasciitis (NF), a severe invasive infection of any of the soft tissue compartments of the body, is characterized by fulminant tissue destruction, systemic signs of toxicity and sepsis and high mortality. The aim of the study was to determine the nature of NF in the Northern Territory of Australia. Methods: A retrospective analysis of all cases of NF over a period of 13 years (January 2000 to December 2012) was carried out. Pathological information was obtained from the Laboratory Information System of the Anatomical Pathology Department at Royal Darwin Hospital and patient demographics and clinical outcome data were retrieved from medical records. Results: A total of 85 cases of histologically proven NF cases were available for analysis. The average age was 48 years and the male to female ratio was 1.6:1. Despite the fact that less than one-third of the population of the Northern Territory is indigenous, more than 50% of the NF patients were indigenous and in this group disease mortality rate was 28%, compared to 17% mortality in the non-indigenous group of patients. The lower extremity was the most common site of infection. Group A streptococcus (GAS) was isolated in 45%, Staphylococcus aureus in 20%, pseudomonas species in 4.7%, mixed bacteria in 25.6% and pure fungi in 4.7%. Surgical intervention and antibiotic administration were the standard method of treatment. Amputation was required in 10% of patients. Mortality was high with almost 25% of patients dying from the infection. Conclusion: NF is a devastating infection associated with high morbidity and mortality. Four distinct monomicrobial and one polymicrobial groups emerged. Pure GAS was the commonest offending organism and a distinct albeit small fungal group was also encountered. Clin Infect Immun. 2016;1(1):2-5 doi: http://dx.doi.org/10.14740/cii38e
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".